WaterSplatting: Fast Underwater 3D Scene Reconstruction Using Gaussian Splatting

TL;DR

WaterSplatting introduces a novel underwater 3D scene reconstruction method combining 3D Gaussian Splatting for geometry with a volumetric medium model, enabling real-time rendering and improved quality over NeRF-based approaches.

Contribution

The paper proposes a dual representation approach that fuses 3D Gaussian Splatting with volumetric scattering modeling for underwater scenes, enabling fast and high-quality reconstruction.

Findings

Outperforms state-of-the-art NeRF methods in rendering quality.

Achieves real-time rendering performance.

Effectively models underwater scattering medium.

Abstract

The underwater 3D scene reconstruction is a challenging, yet interesting problem with applications ranging from naval robots to VR experiences. The problem was successfully tackled by fully volumetric NeRF-based methods which can model both the geometry and the medium (water). Unfortunately, these methods are slow to train and do not offer real-time rendering. More recently, 3D Gaussian Splatting (3DGS) method offered a fast alternative to NeRFs. However, because it is an explicit method that renders only the geometry, it cannot render the medium and is therefore unsuited for underwater reconstruction. Therefore, we propose a novel approach that fuses volumetric rendering with 3DGS to handle underwater data effectively. Our method employs 3DGS for explicit geometry representation and a separate volumetric field (queried once per pixel) for capturing the scattering medium. This dual representation further allows the restoration of the scenes by removing the scattering medium. Our method outperforms state-of-the-art NeRF-based methods in rendering quality on the underwater SeaThru-NeRF dataset. Furthermore, it does so while offering real-time rendering performance, addressing the efficiency limitations of existing methods. Web: https://water-splatting.github.io